# ZeroScope **Zeroscope** is a free and open-source **Text-to-Video** software that uses a text-to-video diffusion model to generate high-quality videos from textual It is a text-to-video diffusion model that generates high-quality videos from textual descriptions. It was created by **Cerspense** and is based on the ModelScope model. ZerosSope is still under development, but it has already produced some impressive results. For example, it can generate videos of people walking, talking, and even dancing. It can also generate videos of scenes from nature, such as forests and beaches. If you are interested in trying ZeroScope, you can find it on GitHub. It is available for Windows, macOS, and Linux. Here are some of the features of ZeroScope: It is free and open-source. **It is based on the ModelScope model, which is one of the most advanced text-to-video diffusion models available.** It can generate high-quality videos from textual descriptions. ZeroScope is still under development, but it has already produced some impressive results. If you are looking for a free and open-source text-to-video software that can generate high-quality videos, Zeroscope is a great option. ### **Technology behind ModelScope:** ModelScope is a “Model-as-a-Service” (MaaS) platform that seeks to bring together most advanced machine learning models from the AI community, and to streamline the process of leveraging AI models in real applications. It provides a model-centric development and application experience, streamlining the support for model training, inference, export and deployment. It also facilitates users to build their own MLOps based on the ModelScope ecosystem. ModelScope offers a wide range of models, including: * Natural language processing (NLP) models, such as BERT, RoBERTa, and XLNet * Computer vision (CV) models, such as ResNet, VGG, and YOLO * Audio models, such as WaveNet and Tacotron * Multi-modality models, such as multimodal transformers and multimodal fusion models * AI for science models, such as AlphaFold and DeepChem ModelScope models are available in a variety of formats, including **PyTorch, TensorFlow, and ONNX.** They can be used in a variety of applications, such as: * Text classification * Natural language inference * Question answering * Object detection * Speech recognition * Medical image analysis * Drug discovery ModelScope is a powerful tool for developers who want to use the latest AI models in their applications. It makes it easy to find, deploy, and use models, and it provides a variety of tools to help developers track and manage their models. Here are some of the benefits of using ModelScope: * Access to the latest AI models * Easy to use and deploy models * A variety of tools to track and manage models * A model-centric development and application experience * A platform for building MLOps If you are looking for a way to use the latest AI models in your applications, then ModelScope is a great option. It is a powerful tool that makes it easy to find, deploy, and use models. {% embed url="" %} {% embed url="" %} {% embed url="" %} **NEWS:** China’s NEW Open Source Zeroscope AI Alarms The Entire Tech Space (NOW ANNOUNCING TTV) Zeroscope is a text to video TTV artificial intelligence that is open source and challenging other top performing solutions like Runway ML. Snapfusion brings text to image diffusion AI models to mobile devices. {% embed url="" %} --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://metaverse-imagen.gitbook.io/ai-tools-research/ai-tools-main-categories/video-and-animation/video-synthesis-generation/zeroscope.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.